| Self-Attentive Sequential Recommendation WC Kang, J McAuley IEEE International Conference on Data Mining (ICDM'18), 2018 | 2637 | 2018 |
| Feature Learning based Deep Supervised Hashing with Pairwise Labels WJ Li, S Wang, WC Kang International Joint Conference on Artificial Intelligence (IJCAI'16), 2016 | 826 | 2016 |
| Translation-based Recommendation R He, WC Kang, J McAuley The ACM Recommender Systems conference (RecSys'17), 2017 | 474 | 2017 |
| Visually-Aware Fashion Recommendation and Design with Generative Image Models WC Kang, C Fang, Z Wang, J McAuley International Conference on Data Mining (ICDM'17), 2017 | 338 | 2017 |
| Column Sampling Based Discrete Supervised Hashing WC Kang, WJ Li, ZH Zhou AAAI Conference on Artificial Intelligence (AAAI'16), 2016 | 308 | 2016 |
| CosRec: 2D Convolutional Neural Networks for Sequential Recommendation A Yan, S Cheng, WC Kang, M Wan, J McAuley ACM International Conference on Information and Knowledge Management (CIKM …, 2019 | 128 | 2019 |
| Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction WC Kang*, J Ni*, N Mehta, M Sathiamoorthy, L Hong, E Chi, DZ Cheng PGAI@CIKM'23, 2023 | 97 | 2023 |
| Complete the Look: Scene-based Complementary Product Recommendation WC Kang, E Kim, J Leskovec, C Rosenberg, J McAuley IEEE Conference on Computer Vision and Pattern Recognition (CVPR'19), 2019 | 93 | 2019 |
| Learning to Embed Categorical Features without Embedding Tables for Recommendation WC Kang, DZ Cheng, T Yao, X Yi, T Chen, L Hong, EH Chi SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'21), Research …, 2021 | 73* | 2021 |
| Candidate Generation with Binary Codes for Large-Scale Top-N Recommendation WC Kang, J McAuley ACM International Conference on Information and Knowledge Management (CIKM'19), 2019 | 68 | 2019 |
| Translation-based Recommendation: A Scalable Method for Modeling Sequential Behavior R He, WC Kang, J McAuley International Joint Conference on Artificial Intelligence (IJCAI'18), Sister …, 2018 | 55 | 2018 |
| Learning Multi-granular Quantized Embeddings for Large-Vocab Categorical Features in Recommender Systems WC Kang, DZ Cheng, T Chen, X Yi, D Lin, L Hong, EH Chi Innovation in Data Science workshop at The Web Conference 2020, IID@WWW'20, 2020 | 54 | 2020 |
| Recommendation Through Mixtures of Heterogeneous Item Relationships WC Kang, M Wan, J McAuley ACM International Conference on Information and Knowledge Management (CIKM'18), 2018 | 47 | 2018 |
| Generating user-customized items using a visually-aware image generation network C Fang, Z Wang, W Kang, J Mcauley US Patent 10,970,765, 2021 | 46 | 2021 |
| Generating visually-aware item recommendations using a personalized preference ranking network C Fang, Z Wang, W Kang, J McAuley US Patent 11,100,400, 2021 | 27 | 2021 |
| Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems B Coleman*, WC Kang*, M Fahrbach, R Wang, L Hong, EH Chi, ... NeurIPS'23, 2023 | 8 | 2023 |
| Learning Consumer and Producer Embeddings for User-Generated Content Recommendation WC Kang, J McAuley The ACM Recommender Systems conference (RecSys'18), 2018 | 7 | 2018 |
| How to Train Data-Efficient LLMs N Sachdeva, B Coleman, WC Kang, J Ni, L Hong, EH Chi, J Caverlee, ... arXiv preprint arXiv:2402.09668, 2024 | 5 | 2024 |
| Farzi Data: Autoregressive Data Distillation N Sachdeva, Z He, WC Kang, J Ni, DZ Cheng, J McAuley arXiv preprint arXiv:2310.09983, 2023 | 5 | 2023 |
| Improving Data Efficiency for Recommenders and LLMs N Sachdeva, B Coleman, WC Kang, J Ni, J Caverlee, L Hong, E Chi, ... Proceedings of the 18th ACM Conference on Recommender Systems, 790-792, 2024 | 1 | 2024 |
Julian McAuleyProfessor, UC San DiegoПотвърден имейл адрес: eng.ucsd.edu
